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Add Conv3DLayer, DeConv3DLayer #3348

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merged 22 commits into from
Aug 31, 2017
Merged

Add Conv3DLayer, DeConv3DLayer #3348

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cfb86c4
Add vol2col and col2vol cuda kernel
chengduoZH Aug 13, 2017
8cc0eb9
Modify ConvConfig, Add depth dimension
chengduoZH Aug 13, 2017
5d7f6dd
Add depth dimension information to ConvBaseLayer
chengduoZH Aug 13, 2017
11975b4
Add Conv3DLayer
chengduoZH Aug 13, 2017
23cf0c6
Add DeConv3DLayer
chengduoZH Aug 13, 2017
52ceeed
Add col2vol and vol2col CPU funtion
chengduoZH Aug 13, 2017
9b3d6ac
Add depth dimension information to Argument
chengduoZH Aug 13, 2017
424b325
add unit test DeConv3D, Conv3D, col2vol, vol2col
chengduoZH Aug 18, 2017
c792ef7
fix DeConv3D, Conv3D
chengduoZH Aug 18, 2017
43f6cdc
fix Matrix
chengduoZH Aug 18, 2017
0a7516d
fix col2vol vol2col kernel
chengduoZH Aug 18, 2017
38cc5da
modified bias shape of ConvLayer
chengduoZH Aug 18, 2017
d5768eb
fix above comments
chengduoZH Aug 18, 2017
f715c74
Add_config_parser_for_Conv3D_DeConv3D
chengduoZH Aug 21, 2017
2710584
fix above comments
chengduoZH Aug 23, 2017
6053f7e
fix previous comments(c++)
chengduoZH Aug 28, 2017
4dcc533
fix conflict
chengduoZH Aug 29, 2017
34f4f76
Update networks.py
Aug 30, 2017
2ae37a4
fix data_layer for 3D data
chengduoZH Aug 30, 2017
2e97045
fix layers_test.py
chengduoZH Aug 31, 2017
a4e1e12
Add test_conv3d_layer.protostr,test_deconv3d_layer.protostr
chengduoZH Aug 31, 2017
455d2bd
fix conflict
chengduoZH Aug 31, 2017
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76 changes: 76 additions & 0 deletions paddle/cuda/include/hl_matrix.h
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Original file line number Diff line number Diff line change
Expand Up @@ -224,4 +224,80 @@ extern void hl_matrix_collect_shared_bias(real* B_d,
extern void hl_matrix_rotate(
real* mat, real* matRot, int dimM, int dimN, bool clockWise);

/**
* @brief Matrix vol2Col: Convert 3D volume into col matrix
*
* @param[in] matSrc input matrix.
* @param[in] channel channel of matSrc.
* @param[in] depth depth of matSrc.
* @param[in] height height of matSrc.
* @param[in] width width of matSrc.
* @param[in] filterD depth of filter.
* @param[in] filterH height of filter.
* @param[in] filterW width of filter.
* @param[in] strideD stride in the depth.
* @param[in] strideH stride in the height.
* @param[in] strideW stride in the width.
* @param[in] paddingD padding in the depth.
* @param[in] paddingH padding in the height.
* @param[in] paddingW padding in the width.
* @param[out] dataDst output matrix.
*
*/
extern void hl_matrix_vol2Col(const real* dataSrc,
int channels,
int depth,
int height,
int width,
int filterD,
int filterH,
int filterW,
int strideD,
int strideH,
int strideW,
int paddingD,
int paddingH,
int paddingW,
real* dataDst);

/**
* @brief Matrix col2Vol: Convert col matrix into 3D volume
*
* @param[out] matDst output matrix.
* @param[in] channel channel of matDst.
* @param[in] depth depth of matDst.
* @param[in] height height of matDst.
* @param[in] width width of matDst.
* @param[in] filterD depth of filter.
* @param[in] filterH height of filter.
* @param[in] filterW width of filter.
* @param[in] strideD stride in the depth.
* @param[in] strideH stride in the height.
* @param[in] strideW stride in the width.
* @param[in] paddingD padding in the depth.
* @param[in] paddingH padding in the height.
* @param[in] paddingW padding in the width.
* @param[in] matSrc input matrix.
* @param[in] beta input
* @param[in] alpha input
*
*/
extern void hl_matrix_col2Vol(real* dataDst,
int channels,
int depth,
int height,
int width,
int filterD,
int filterH,
int filterW,
int strideD,
int strideH,
int strideW,
int paddingD,
int paddingH,
int paddingW,
const real* dataSrc,
real alpha,
real beta);

#endif /* HL_MATRIX_H_ */
34 changes: 34 additions & 0 deletions paddle/cuda/include/stub/hl_matrix_stub.h
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Original file line number Diff line number Diff line change
Expand Up @@ -99,4 +99,38 @@ inline void hl_matrix_collect_shared_bias(real* B_d,
inline void hl_matrix_rotate(
real* mat, real* matRot, int dimM, int dimN, bool clockWise) {}

inline void hl_matrix_vol2Col(const real* dataSrc,
int channels,
int depth,
int height,
int width,
int filterD,
int filterH,
int filterW,
int strideD,
int strideH,
int strideW,
int paddingD,
int paddingH,
int paddingW,
real* dataDst) {}

inline void hl_matrix_col2Vol(real* dataDst,
int channels,
int depth,
int height,
int width,
int filterD,
int filterH,
int filterW,
int strideD,
int strideH,
int strideW,
int paddingD,
int paddingH,
int paddingW,
const real* dataSrc,
real alpha,
real beta) {}

#endif // HL_MATRIX_STUB_H_
201 changes: 201 additions & 0 deletions paddle/cuda/src/hl_cuda_matrix.cu
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Original file line number Diff line number Diff line change
Expand Up @@ -592,3 +592,204 @@ void hl_matrix_rotate(
mat, matRot, dimM, dimN, clockWise);
CHECK_SYNC("hl_matrix_rotate failed");
}

__global__ void keMatrixVol2Col(int num_kernels,
const real* dataSrc,
real* dataDst,
int depth,
int height,
int width,
int filterD,
int filterH,
int filterW,
int strideD,
int strideH,
int strideW,
int paddingD,
int paddingH,
int paddingW,
int depth_col,
int height_col,
int width_col) {
for (int index = blockIdx.x * blockDim.x + threadIdx.x; index < num_kernels;
index += blockDim.x * gridDim.x) {
int w_out = index % width_col;
int h_out = (index / width_col) % height_col;
int d_out = (index / width_col / height_col) % depth_col;
int channel_in = index / width_col / height_col / depth_col;
int channel_out = channel_in * filterD * filterH * filterW;
int w_in = w_out * strideW - paddingW;
int h_in = h_out * strideH - paddingH;
int d_in = d_out * strideD - paddingD;

dataDst +=
((channel_out * depth_col + d_out) * height_col + h_out) * width_col +
w_out;
dataSrc += ((channel_in * depth + d_in) * height + h_in) * width + w_in;
for (int k = 0; k < filterD; ++k) {
for (int i = 0; i < filterH; ++i) {
for (int j = 0; j < filterW; ++j) {
int d = d_in + k;
int h = h_in + i;
int w = w_in + j;
*dataDst = (d >= 0 && d < depth && h >= 0 && h < height && w >= 0 &&
w < width)
? dataSrc[(k * height + i) * width + j]
: 0;
dataDst += depth_col * height_col * width_col;
}
}
}
}
}

void hl_matrix_vol2Col(const real* dataSrc,
int channels,
int depth,
int height,
int width,
int filterD,
int filterH,
int filterW,
int strideD,
int strideH,
int strideW,
int paddingD,
int paddingH,
int paddingW,
real* dataDst) {
int depth_col = (depth + 2 * paddingD - filterD) / strideD + 1;
int height_col = (height + 2 * paddingH - filterH) / strideH + 1;
int width_col = (width + 2 * paddingW - filterW) / strideW + 1;
int num_kernels = channels * depth_col * height_col * width_col;

const int threads = 512;
const int blocks = DIVUP(num_kernels, threads);

keMatrixVol2Col<<<blocks, threads, 0, STREAM_DEFAULT>>>(num_kernels,
dataSrc,
dataDst,
depth,
height,
width,
filterD,
filterH,
filterW,
strideD,
strideH,
strideW,
paddingD,
paddingH,
paddingW,
depth_col,
height_col,
width_col);
CHECK_SYNC("hl_matrix_vol2Col failed");
}

__global__ void keMatrixCol2Vol(int num_kernels,
real* dataDst,
const real* dataSrc,
int depth,
int height,
int width,
int filterD,
int filterH,
int filterW,
int strideD,
int strideH,
int strideW,
int paddingD,
int paddingH,
int paddingW,
int depth_col,
int height_col,
int width_col,
real alpha,
real beta) {
for (int index = blockIdx.x * blockDim.x + threadIdx.x; index < num_kernels;
index += blockDim.x * gridDim.x) {
real srcVal = 0;
real dstVal = dataDst[index];
int w = index % width + paddingW;
int h = (index / width) % height + paddingH;
int d = (index / width / height) % depth + paddingD;
int c = index / width / height / depth;
// compute the start and end of the output
int w_col_start = (w < filterW) ? 0 : (w - filterW) / strideW + 1;
int w_col_end = min(w / strideW + 1, width_col);
int h_col_start = (h < filterH) ? 0 : (h - filterH) / strideH + 1;
int h_col_end = min(h / strideH + 1, height_col);
int d_col_start = (d < filterD) ? 0 : (d - filterD) / strideD + 1;
int d_col_end = min(d / strideD + 1, depth_col);

int offset = (c * filterD * filterW * filterH + d * filterW * filterH +
h * filterW + w) *
depth_col * height_col * width_col;

int coeff_d_col =
(1 - strideD * filterW * filterH * depth_col) * height_col * width_col;
int coeff_h_col =
(1 - strideH * filterW * depth_col * height_col) * width_col;
int coeff_w_col = (1 - strideW * depth_col * height_col * width_col);

for (int d_col = d_col_start; d_col < d_col_end; ++d_col) {
for (int h_col = h_col_start; h_col < h_col_end; ++h_col) {
for (int w_col = w_col_start; w_col < w_col_end; ++w_col) {
srcVal += dataSrc[offset + d_col * coeff_d_col + h_col * coeff_h_col +
w_col * coeff_w_col];
}
}
}
dataDst[index] = alpha * srcVal + beta * dstVal;
}
}

void hl_matrix_col2Vol(real* dataDst,
int channels,
int depth,
int height,
int width,
int filterD,
int filterH,
int filterW,
int strideD,
int strideH,
int strideW,
int paddingD,
int paddingH,
int paddingW,
const real* dataSrc,
real alpha,
real beta) {
int depth_col = (depth + 2 * paddingD - filterD) / strideD + 1;
int height_col = (height + 2 * paddingH - filterH) / strideH + 1;
int width_col = (width + 2 * paddingW - filterW) / strideW + 1;
int num_kernels = channels * depth * height * width;

const int threads = 512;
const int blocks = DIVUP(num_kernels, threads);

keMatrixCol2Vol<<<blocks, threads, 0, STREAM_DEFAULT>>>(num_kernels,
dataDst,
dataSrc,
depth,
height,
width,
filterD,
filterH,
filterW,
strideD,
strideH,
strideW,
paddingD,
paddingH,
paddingW,
depth_col,
height_col,
width_col,
alpha,
beta);

CHECK_SYNC("hl_matrix_col2Vol failed");
}
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